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Interest in higher education institutions (HEIs) as instruments for development has increased in recent years. The main objective of this paper is to address the contribution of HEIs to development through their missions, models, and challenges. With this purpose, we perform a historical analysis and characterise higher-education systems through the perspective of university models and missions, noticing relevant aspects regarding the evolution of this institution over time, as well as the transformations undergone. We also consider the main challenges that current higher education systems face in the 21st century. As methodological approaches, we carry out a literature review complemented by a comparative analysis based on data from the higher education systems of ten European countries. The findings show that HEIs can contribute to development through their missions, which are related to the models of higher education. Their first mission (teaching) contributes to improving human capital and attracting highly qualified people to their regions; the second mission (research) improves scientific knowledge which can foster innovative activities; and the third mission (community service) acts as a link between research and business, including patents, business incubators, and collaboration agreements. We also conclude that the challenges of higher education in the 21st century can be categorised essentially in three main areas: (1) globalisation and massification of higher education, as well as the internationalisation of HEIs' missions and diversification of the educational supply to attract new students; (2) new technologies related to the digitalisation of teaching and distance learning; and (3) higher education entrepreneurship, showing the importance of university-company relationships. This paper provides a global setting for a reflection on the role of HEIs in the 21st century, given their connection with society and the need for a more effective contribution to socio-economic development.

Context: Existing studies have explored the association between workplace training and wages suggesting that training participation may have a positive association with wages. However, we still know very little about whether this association varies between men and women. Through its potential positive association with wages, training may balance wage differences between men and women. In addition, the gender wage gap varies across the wage distribution. Differences in the association between training participation and wages for men and women across the earnings spectrum may offer an explanation as to why the discrepancy in female/male earnings is larger at some point of the wage distribution compared to others. Approach: Using data from the Programme for International Assessment of Adult Competencies (PIAAC) and unconditional quantile regression, this paper examines whether the association between workplace training and wages differs between men and women at different points of the wage distribution across 14 European countries. To partly control for endogeneity in training participation, detailed measures of cognitive skills have been included in the models. Findings: Findings show gender differences in the association between training and wages across the wage distribution. In most countries, results indicate larger training coefficients for women than men at the lower end of the wage spectrum whereas they are larger for men at the top. This pattern holds across most countries with the only exception of Liberal ones, where women benefit less than men across the entire wage spectrum. Conclusions: The findings of this work reveal that distributional variations in returns to workplace training follow a similar pattern across industrialized countries, despite their different institutional settings. Moreover, differences in training coefficients of men and women at different parts of the wage distribution suggest that training could reduce gender wage differences among low earners and potentially widen the gap in wages among individuals at the top of the wage distribution.

Education is the core of the factors that improved people for a better lifestyle and increases the level of society' development. Quality education is one of the most vital goals of Sustainable Development Goals (SDGs) due to actualizing these factors. Using relational network data envelopment analysis (DEA), which have three interrelated substages, this current paper computes the educational economy efficiency of the Organisation for Economic Co-operation and Development (OECD) countries bearing in mind the characteristics related to SDGs. The contribution of our study is the use of a novel approach to computing the educational economy efficiency using relational network DEA with GAMS. Even though some interesting differences reveal in the efficiency of the countries, the findings show that countries with high-efficiency scores are clustered around countries like Latvia, Slovenia, and Korea.

In this paper, I examine whether generalized trust and education, as well as social security policies of welfare state institutions matter for cross-national differences in subjective well-being (SWB), because knowledge on this issue is still lacking. For this purpose I integrated the insights of two sociological theories: Social Function Production theory and Actor-Centred Institutionalism. Based on these theoretical notions we derived several hypotheses, which I tested using multilevel analysis of the data from the European Social Survey (2006), in a sample of 37,237 respondents from 22 European countries. My findings indicate that various extensiveness of social security policies matter for the level of SWB, and for the impact of education on SWB. I found negative impact of low education on SWB in all countries, except in Northern and Western European countries. This might suggest that social security policies of the latter countries have diminished the negative impact of low education on SWB. Moreover, my findings indicate positive relationship between individual education and generalized trust; as well as between generalized trust and SWB in countries with all five types of social security policies.

Background: Data from the Programme for the International Assessment of Adult Competencies (PIAAC) revealed that countries systematically differ in their respondents' literacy, numeracy, and problem solving in technology-rich environments skills; skill levels also vary by gender, age, level of education or migration background. Similarly, systematic differences have been documented with respect to adults' participation in education, which can be considered as a means to develop and maintain skills. From a psychological perspective, motivation to learn is considered a key factor associated with both skill development and participation in (further) education. In order to account for motivation when analyzing PIAAC data, four items from the PIAAC background questionnaire were recently compiled into a motivation-to-learn scale. This scale has been found to be invariant (i.e., showing full weak and partial strong measurement invariance) across 21 countries. Methods: This paper presents further analyses using multiple-group graded response models to scrutinize the validity of the motivation-to-learn scale for group comparisons. Results: Results indicate at least partial strong measurement invariance across gender, age groups, level of education, and migration background in most countries under study (all CFI > 0.95, all RMSEA < 0.08). Thus, the scale is suitable for comparing both means and associations across these groups. Conclusions:Results are discussed in light of country characteristics, challenges of measurement invariance testing, and potential future research using PIAAC data.

When investigating the association between brain tumors and use of mobile telephones, accurate data on tumor position are essential, due to the highly localized absorption of energy in the human brain from the radio-frequency fields emitted. We used a point process model to investigate this association using information that included tumor localization data from the INTERPHONE Study (Australia, Canada, Denmark, Finland, France, Germany, Israel, Italy, Japan, New Zealand, Norway, Sweden, and the United Kingdom). Our main analysis included 792 regular mobile phone users diagnosed with a glioma between 2000 and 2004. Similar to earlier results, we found a statistically significant association between the intracranial distribution of gliomas and the self-reported location of the phone. When we accounted for the preferred side of the head not being exclusively used for all mobile phone calls, the results were similar. The association was independent of the cumulative call time and cumulative number of calls. However, our model used reported side of mobile phone use, which is potentially influenced by recall bias. The point process method provides an alternative to previously used epidemiologic research designs when one is including localization in the investigation of brain tumors and mobile phone use. [ABSTRACT FROM AUTHOR]

Background: Healthy life years have superseded life expectancy (LE) as the most important indicator for population health. The most common approach to separate the total number of life years into those spent in good and poor health is the Sullivan method which incorporates the health dimension to the classic period life table, thus transforming the LE indicator into the health expectancy (HE) indicator. However, life years derived from a period life table and health prevalence derived from survey data are based on different conceptual frameworks. Method: We modify the Sullivan method by combining the health prevalence data with the conceptually better fitting cross-sectional average length of life (CAL). We refer to this alternative HE indicator as the "cross-sectional average length of healthy life" (HCAL). We compare results from this alternative indicator with the conventional Sullivan approach for nine European countries. The analyses are based on EU-SILC data in three empirical applications, including the absolute and relative level of healthy life years, changes between 2008 and 2014, and the extent of the gender gap. Results: HCAL and conventional HE differ in each of these empirical applications. In general, HCAL provides larger gains in healthy life years in recent years, but at the same time greater declines in the proportion of healthy life years. Regarding the gender gap, HCAL provides a more favourable picture for women compared to conventional HE. Nonetheless, the extent of these differences between the indicators is only of minor extent. Conclusions: Albeit the differences between HE and HCAL are small, we found some empirical examples in which the two indicators led to different conclusions. It is important to note, however, that the measurement of health and the data quality are much more important for the healthy life years indicator than the choice of the variant of the Sullivan method. Nonetheless, we suggest to use HCAL in addition to HE whenever possible because it widens the spectrum of empirical analyses and serves for verification of results based on the highly sensitive HE indicator. [ABSTRACT FROM AUTHOR]